Abstract
Korean traditional medicine has obtained more attention from the public and IT service industry especially after ’Dong-eui-bo-gam’ was registered to UNESCO Memory of the World. However, there are many obstacles in developing and commercializing an on-line self-diagnosis system by Korean traditional medicine. From the service point of view, since people are accustomed to the westernized style of diagnosis (symptom-disease pair), it is not easy to understand what traditional Korean medicine diagnoses and how one can react. Technically speaking, we need a special symptom-disease database because Korean traditional medicine has been built upon the innate characteristics of Korean people’s body. Thus, in this paper, we propose a self-diagnosis system of Korean traditional medicine based on Korean Standard Causes of Death Disease Classification Index (KCD) and fuzzy ART/inference method. Since this is for self-diagnosis, our system has graphical user-friendly interface that accepts symptoms of user from a certain part of body where the user feels inconvenient. Then, fuzzy ART algorithm and fuzzy inference engine picks up five most probable diseases with their causes and treatments extracted from Korean traditional medicine books. The power of our system comes from a fuzzy inference module combined with fuzzy ART algorithm that helps classifying related disease from database with accuracy. Our system is verified by field experts of Korean traditional medicine in collecting symptom-disease-treatments relationships and performance evaluation of experiment results.
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References
Kim, Y.S.: Dong-eui-bo-gam. Solbit Publications (2003)
N.T.T.C. for Health Personnel, Medical Treatments for Family Doctors. Seoul National University (1993)
Lee, S.J.: Dong-eui-bo-gam by Symptoms. Obi Enterprise (2004)
Lee, C.H.: Chinese Medicine. Minjoong Seogwan (1999)
Han, K.T., Kim, H.C., Ko, J.Y., Lee, C.W.: Real-time intrusion detection using fuzzy adaptive resonance theory. The Journal of Korean Institute of Information Scientists and Engineers 28(2), 640–642 (2001)
Kim, K.B., Kim, M.N., Woo, Y.W., Noh, H.C., Shin, S.H.: Self health diagnosis system of oriental medicine using fuzzy inference method. In: Proceeding of Winter Conference, pp. 207–211. Korea Society of Computer Information (2010)
Kim, K.B., Kim, M.N., Cho, S.K., Noh, H.C.: Self health diagnosis system of oriental medicine using enhanced fuzzy ART algorithm. In: Proceeding of Summer Conference, pp. 329–332. Korea Society of Computer Information (2009)
Kim, K.-B., Kim, S., Sim, K.-B.: Nucleus Classification and Recognition of Uterine Cervical Pap-Smears Using Fuzzy ART Algorithm. In: Wang, T.-D., Li, X., Chen, S.-H., Wang, X., Abbass, H.A., Iba, H., Chen, G.-L., Yao, X. (eds.) SEAL 2006. LNCS, vol. 4247, pp. 560–567. Springer, Heidelberg (2006)
Kim, K.B., Woo, Y.W., Kim, J.S.: Self disease diagnosis system using enhanced ART2 algorithm. The Journal of The Korea Institute of Maritime Information and Communication Sciences 11(11), 2150–2157 (2007)
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Kim, KB., Kim, JW. (2012). Self Health Diagnosis System with Korean Traditional Medicine Using Fuzzy ART and Fuzzy Inference Rules. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Intelligent Information and Database Systems. ACIIDS 2012. Lecture Notes in Computer Science(), vol 7198. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28493-9_35
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DOI: https://doi.org/10.1007/978-3-642-28493-9_35
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